Aleksandar Tomic
Staff Software Engineer at Databricks
Belgrade, Central Serbia
Summary
🤩
Rockstar🎓
Top SchoolAleksandar Tomic is a Staff Software Engineer based in Belgrade with a strong track record in high-scale data and cloud platforms, currently contributing at Databricks after several senior engineering and leadership roles at Microsoft. He has hands-on experience across Azure Data, Serverless SQL, and Azure SQL Managed Instance, blending technical leadership with deep backend engineering. Aleksandar contributes to prominent open-source projects like Apache Spark, where he optimized SQL error handling, date parsing performance, and introduced collation support—work that touches widely used large-scale analytics tooling. Known for fixing subtle performance and correctness issues, he brings a pragmatic focus on robustness and efficiency in distributed systems. Trained in computer software engineering at the University of Belgrade, he combines production-grade engineering with research-oriented problem solving.
2 years of coding experience
12 years of employment as a software developer
BS, Computer Software Engineering, BS, Computer Software Engineering at Univerzitet u Beogradu
Github Skills (11)
big-data10
spark10
collation10
sql10
back-end-development10
scala10
java7
javas7
data-structure5
algorithms5
data-structures5
Programming languages (1)
Github contributions (2)
apache/spark
Nov 2023 - Nov 2024
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:326 reviews, 18 PRs, 315 comments in 11 months
Contributions summary:Aleksandar primarily worked on improving the `raise_error` function within the SQL component of Apache Spark, removing an error-class parameter and reverting to a single-parameter approach. They also addressed a performance issue in date parsing by optimizing the `StringToDate` function to avoid unnecessary calls to `trimAll`. Furthermore, they implemented changes related to collation, introducing `collate` and `collation` expressions and ensuring proper functionality for aggregates and joins with non-binary collations.
analyticspythondata-processingsqlapache
dbatomic/spark
Nov 2023 - Mar 2025
Apache Spark - A unified analytics engine for large-scale data processing
Contributions:9 reviews, 3 PRs, 175 pushes in 1 year 4 months
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